ParEvalLayer: When Partial LLM-Agent Evaluations Support a Decision

LLM-agent evaluations often produce task outcomes long before the full benchmark run is complete. A partial score is tempting to report, but it does not show whether the observed tasks support the same conclusion as the completed evaluation. Early tasks can omit important parts of a benchmark, running cheaper tasks first can distort the observed sample, and a rule that decides only easy pairs can appear accurate while leaving many comparisons unresolved. We introduce ParEvalLayer, a decision lay

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ethics.ai (3 August 2026), “ParEvalLayer: When Partial LLM-Agent Evaluations Support a Decision,” evidence record 16095, https://ethics.ai/record/16095 (originally published by arXiv cs.AI).

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